mirror of
https://github.com/LostRuins/koboldcpp.git
synced 2025-09-11 09:34:37 +00:00
implment vision model architecture, gguf convertor
This commit is contained in:
HimariO
parent
558a764713
commit
d9f2d71bc2
3 changed files with 219 additions and 83 deletions
|
|
@ -169,6 +169,7 @@ struct clip_hparams {
|
|||
std::vector<int32_t> image_grid_pinpoints;
|
||||
int32_t image_crop_resolution;
|
||||
std::unordered_set<int32_t> vision_feature_layer;
|
||||
std::vector<int32_t> full_attn_layers;
|
||||
};
|
||||
|
||||
struct clip_layer {
|
||||
|
|
@ -200,6 +201,9 @@ struct clip_layer {
|
|||
struct ggml_tensor * ff_down_w = nullptr;
|
||||
struct ggml_tensor * ff_down_b = nullptr;
|
||||
|
||||
struct ggml_tensor * ff_g_w = NULL;
|
||||
struct ggml_tensor * ff_g_b = NULL;
|
||||
|
||||
// layernorm 2
|
||||
struct ggml_tensor * ln_2_w = nullptr;
|
||||
struct ggml_tensor * ln_2_b = nullptr;
|
||||
|
|
@ -324,6 +328,9 @@ struct clip_ctx {
|
|||
float image_std[3];
|
||||
bool use_gelu = false;
|
||||
bool use_silu = false;
|
||||
bool use_glu_mlp = false;
|
||||
bool use_rms_norm = false;
|
||||
int32_t ftype = 1;
|
||||
|
||||
gguf_context_ptr ctx_gguf;
|
||||
ggml_context_ptr ctx_data;
|
||||
|
|
@ -810,6 +817,7 @@ static ggml_cgraph * clip_image_build_graph_legacy(clip_ctx * ctx, const clip_im
|
|||
const int n_head = hparams.n_head;
|
||||
const int d_head = hidden_size / n_head;
|
||||
const float eps = hparams.eps;
|
||||
const bool use_window_attn = hparams.full_attn_layers.size() > 0;
|
||||
int mrope_sections[4] = {d_head/4, d_head/4, d_head/4, d_head/4};
|
||||
|
||||
const int batch_size = imgs.entries.size();
|
||||
|
|
@ -862,8 +870,10 @@ static ggml_cgraph * clip_image_build_graph_legacy(clip_ctx * ctx, const clip_im
|
|||
// inp = ggml_add(ctx0, inp, ggml_repeat(ctx0, model.patch_bias, inp));
|
||||
inp = ggml_add(ctx0, inp, model.patch_bias);
|
||||
}
|
||||
struct ggml_tensor * embeddings = inp;
|
||||
struct ggml_tensor * pos_embed = nullptr;
|
||||
struct ggml_tensor * embeddings = inp;
|
||||
struct ggml_tensor * pos_embed = nullptr;
|
||||
struct ggml_tensor * window_mask = nullptr;
|
||||
struct ggml_tensor * window_idx = nullptr;
|
||||
|
||||
if (ctx->has_llava_projector) {
|
||||
// concat class_embeddings and patch_embeddings
|
||||
|
|
@ -915,6 +925,28 @@ static ggml_cgraph * clip_image_build_graph_legacy(clip_ctx * ctx, const clip_im
|
|||
const auto & vision_feature_layer = hparams.vision_feature_layer;
|
||||
|
||||
// loop over layers
|
||||
|
||||
if (use_window_attn) {
|
||||
window_idx = ggml_new_tensor_1d(ctx0, GGML_TYPE_I32, num_positions / 4);
|
||||
ggml_set_name(window_idx, "window_idx");
|
||||
ggml_set_input(window_idx);
|
||||
|
||||
// mask for window attention
|
||||
window_mask = ggml_new_tensor_2d(ctx0, GGML_TYPE_F32, num_positions, num_positions);
|
||||
ggml_set_name(window_mask, "window_mask");
|
||||
ggml_set_input(window_mask);
|
||||
|
||||
// embeddings shape: [hidden_size, patches_w * patches_h, batch_size]
|
||||
GGML_ASSERT(batch_size == 1);
|
||||
embeddings = ggml_reshape_2d(ctx0, embeddings, hidden_size * 4, patches_w * patches_h * batch_size / 4);
|
||||
embeddings = ggml_get_rows(ctx0, embeddings, window_idx);
|
||||
embeddings = ggml_reshape_3d(ctx0, embeddings, hidden_size, patches_w * patches_h, batch_size);
|
||||
|
||||
positions = ggml_reshape_2d(ctx0, positions, 16, num_position_ids / 4 / 4);
|
||||
positions = ggml_get_rows(ctx0, positions, window_idx);
|
||||
positions = ggml_reshape_1d(ctx0, positions, num_position_ids);
|
||||
}
|
||||
|
||||
for (int il = 0; il < ctx->max_feature_layer; il++) {
|
||||
struct ggml_tensor * cur = embeddings; // embeddings = residual, cur = hidden_states
|
||||
|
||||
|
|
@ -927,9 +959,12 @@ static ggml_cgraph * clip_image_build_graph_legacy(clip_ctx * ctx, const clip_im
|
|||
//const size_t nb_q_w = model.layers[il].q_w->nb[0];
|
||||
|
||||
// layernorm1
|
||||
{
|
||||
if (ctx->use_rms_norm) {
|
||||
cur = ggml_rms_norm(ctx0, cur, eps);
|
||||
cur = ggml_mul(ctx0, cur, model.layers[il].ln_1_w);
|
||||
}
|
||||
else {
|
||||
cur = ggml_norm(ctx0, cur, eps);
|
||||
|
||||
cur = ggml_add(ctx0, ggml_mul(ctx0, cur, model.layers[il].ln_1_w),
|
||||
model.layers[il].ln_1_b);
|
||||
}
|
||||
|
|
@ -969,7 +1004,14 @@ static ggml_cgraph * clip_image_build_graph_legacy(clip_ctx * ctx, const clip_im
|
|||
V = ggml_reshape_3d(ctx0, V, num_positions, d_head, n_head * batch_size);
|
||||
|
||||
struct ggml_tensor * KQ = ggml_mul_mat(ctx0, K, Q);
|
||||
KQ = ggml_soft_max_ext(ctx0, KQ, nullptr, 1.0f / sqrtf((float)d_head), 0.0f);
|
||||
const bool inlist = std::find(hparams.full_attn_layers.begin(), hparams.full_attn_layers.end(), il) != hparams.full_attn_layers.end();
|
||||
const bool full_attn = use_window_attn ? inlist : true;
|
||||
if (full_attn) {
|
||||
KQ = ggml_soft_max_ext(ctx0, KQ, nullptr, 1.0f / sqrtf((float)d_head), 0.0f);
|
||||
} else {
|
||||
KQ = ggml_soft_max_ext(ctx0, KQ, window_mask, 1.0f, 0.0f);
|
||||
}
|
||||
|
||||
struct ggml_tensor * KQV = ggml_mul_mat(ctx0, V, KQ);
|
||||
KQV = ggml_reshape_4d(ctx0, KQV, d_head, num_positions, n_head, batch_size);
|
||||
KQV = ggml_permute(ctx0, KQV, 0, 2, 1, 3);
|
||||
|
|
@ -986,25 +1028,50 @@ static ggml_cgraph * clip_image_build_graph_legacy(clip_ctx * ctx, const clip_im
|
|||
embeddings = cur; // embeddings = residual, cur = hidden_states
|
||||
|
||||
// layernorm2
|
||||
{
|
||||
if (ctx->use_rms_norm) {
|
||||
cur = ggml_rms_norm(ctx0, cur, eps);
|
||||
cur = ggml_mul(ctx0, cur, model.layers[il].ln_2_w);
|
||||
} else {
|
||||
cur = ggml_norm(ctx0, cur, eps);
|
||||
|
||||
cur = ggml_add(ctx0, ggml_mul(ctx0, cur, model.layers[il].ln_2_w), model.layers[il].ln_2_b);
|
||||
}
|
||||
|
||||
cur = ggml_mul_mat(ctx0, model.layers[il].ff_i_w, cur);
|
||||
cur = ggml_add(ctx0, cur, model.layers[il].ff_i_b);
|
||||
// mlp
|
||||
if (ctx->use_glu_mlp) {
|
||||
// ffn_up
|
||||
auto cur_up = ggml_mul_mat(ctx0, model.layers[il].ff_o_w, cur);
|
||||
cur_up = ggml_add(ctx0, cur_up, model.layers[il].ff_o_b);
|
||||
|
||||
if (ctx->use_gelu) {
|
||||
cur = ggml_gelu_inplace(ctx0, cur);
|
||||
} else if (ctx->use_silu) {
|
||||
cur = ggml_silu_inplace(ctx0, cur);
|
||||
} else {
|
||||
cur = ggml_gelu_quick_inplace(ctx0, cur);
|
||||
auto cur_gate = ggml_mul_mat(ctx0, model.layers[il].ff_g_w, cur);
|
||||
cur_gate = ggml_add(ctx0, cur_gate, model.layers[il].ff_g_b);
|
||||
if (ctx->use_gelu) {
|
||||
cur_gate = ggml_gelu_inplace(ctx0, cur_gate);
|
||||
} else if (ctx->use_silu) {
|
||||
cur_gate = ggml_silu_inplace(ctx0, cur_gate);
|
||||
} else {
|
||||
cur_gate = ggml_gelu_quick_inplace(ctx0, cur_gate);
|
||||
}
|
||||
cur = ggml_mul(ctx0, cur_gate, cur_up);
|
||||
|
||||
// ffn_down
|
||||
cur = ggml_mul_mat(ctx0, model.layers[il].ff_i_w, cur);
|
||||
cur = ggml_add(ctx0, cur, model.layers[il].ff_i_b);
|
||||
}
|
||||
else {
|
||||
cur = ggml_mul_mat(ctx0, model.layers[il].ff_i_w, cur);
|
||||
cur = ggml_add(ctx0, cur, model.layers[il].ff_i_b);
|
||||
|
||||
cur = ggml_mul_mat(ctx0, model.layers[il].ff_o_w, cur);
|
||||
cur = ggml_add(ctx0, cur, model.layers[il].ff_o_b);
|
||||
if (ctx->use_gelu) {
|
||||
cur = ggml_gelu_inplace(ctx0, cur);
|
||||
} else if (ctx->use_silu) {
|
||||
cur = ggml_silu_inplace(ctx0, cur);
|
||||
} else {
|
||||
cur = ggml_gelu_quick_inplace(ctx0, cur);
|
||||
}
|
||||
|
||||
cur = ggml_mul_mat(ctx0, model.layers[il].ff_o_w, cur);
|
||||
cur = ggml_add(ctx0, cur, model.layers[il].ff_o_b);
|
||||
}
|
||||
|
||||
// residual 2
|
||||
cur = ggml_add(ctx0, embeddings, cur);
|
||||
|
|
@ -1014,10 +1081,17 @@ static ggml_cgraph * clip_image_build_graph_legacy(clip_ctx * ctx, const clip_im
|
|||
|
||||
// post-layernorm
|
||||
if (model.post_ln_w) {
|
||||
embeddings = ggml_norm(ctx0, embeddings, eps);
|
||||
ggml_set_name(embeddings, "post_ln");
|
||||
if (ctx->use_rms_norm) {
|
||||
embeddings = ggml_rms_norm(ctx0, embeddings, eps);
|
||||
ggml_set_name(embeddings, "post_ln");
|
||||
|
||||
embeddings = ggml_add(ctx0, ggml_mul(ctx0, embeddings, model.post_ln_w), model.post_ln_b);
|
||||
embeddings = ggml_mul(ctx0, embeddings, model.post_ln_w);
|
||||
} else {
|
||||
embeddings = ggml_norm(ctx0, embeddings, eps);
|
||||
ggml_set_name(embeddings, "post_ln");
|
||||
|
||||
embeddings = ggml_add(ctx0, ggml_mul(ctx0, embeddings, model.post_ln_w), model.post_ln_b);
|
||||
}
|
||||
}
|
||||
|
||||
// final layer is a vision feature layer
|
||||
|
|
@ -1331,6 +1405,18 @@ static ggml_cgraph * clip_image_build_graph_legacy(clip_ctx * ctx, const clip_im
|
|||
embeddings = ggml_add(ctx0, embeddings, model.mm_1_b);
|
||||
}
|
||||
|
||||
if (use_window_attn) {
|
||||
struct ggml_tensor * inv_window_idx = ggml_new_tensor_1d(ctx0, GGML_TYPE_I32, num_positions / 4);
|
||||
ggml_set_name(inv_window_idx, "inv_window_idx");
|
||||
ggml_set_input(inv_window_idx);
|
||||
|
||||
// embeddings shape: [hidden_size, patches_w * patches_h, batch_size]
|
||||
GGML_ASSERT(batch_size == 1);
|
||||
embeddings = ggml_reshape_2d(ctx0, embeddings, hparams.projection_dim, patches_w * patches_h / 4);
|
||||
embeddings = ggml_get_rows(ctx0, embeddings, inv_window_idx);
|
||||
embeddings = ggml_reshape_3d(ctx0, embeddings, hparams.projection_dim, patches_w * patches_h / 4, batch_size);
|
||||
}
|
||||
|
||||
// build the graph
|
||||
ggml_build_forward_expand(gf, embeddings);
|
||||
|
||||
|
|
@ -1447,6 +1533,8 @@ struct clip_model_loader {
|
|||
|
||||
get_bool(KEY_USE_GELU, ctx_clip.use_gelu, false);
|
||||
get_bool(KEY_USE_SILU, ctx_clip.use_silu, false);
|
||||
get_bool(KEY_USE_GLU_MLP, ctx_clip.use_glu_mlp, false);
|
||||
get_bool(KEY_USE_RMS_NORM, ctx_clip.use_rms_norm, false);
|
||||
|
||||
get_u32(string_format(KEY_N_EMBD, "vision"), hparams.hidden_size);
|
||||
get_u32(string_format(KEY_N_HEAD, "vision"), hparams.n_head);
|
||||
|
|
@ -1458,6 +1546,7 @@ struct clip_model_loader {
|
|||
get_u32(KEY_PATCH_SIZE, hparams.patch_size);
|
||||
get_u32(KEY_IMAGE_CROP_RESOLUTION, hparams.image_crop_resolution, false);
|
||||
get_arr_int(KEY_IMAGE_GRID_PINPOINTS, hparams.image_grid_pinpoints, false);
|
||||
get_arr_int(KEY_FULLATTN_BLK_IDX, hparams.full_attn_layers, false);
|
||||
|
||||
{
|
||||
std::string mm_patch_merge_type;
|
||||
|
|
@ -1603,8 +1692,10 @@ struct clip_model_loader {
|
|||
// legacy naming (the in and out is reversed! don't ask me why)
|
||||
layer.ff_i_w = layer.ff_down_w;
|
||||
layer.ff_o_w = layer.ff_up_w;
|
||||
layer.ff_g_w = layer.ff_gate_b;
|
||||
layer.ff_i_b = layer.ff_down_b;
|
||||
layer.ff_o_b = layer.ff_up_b;
|
||||
layer.ff_g_b = layer.ff_gate_b;
|
||||
}
|
||||
|
||||
switch (ctx_clip.proj_type) {
|
||||
|
|
|
|||
Loading…
Add table
Add a link
Reference in a new issue